Determinants of Distress Among Residents During COVID

Annals of Clinical and Medical
Case Reports
Research Article ISSN 2639-8109 Volume 8
Prevalence and Determinants of Distress Among Residents During COVID Crisis
Pamela Houeiss1,2
1
Laboratory Immunology of Diabetes, Cochin Institute, Department EMD, INSERMU1016, Paris, France
2
Medical Faculty, Paris University, Paris, France
*
Corresponding author:
Pamela Houeiss,
Laboratory Immunology of Diabetes, Cochin
Institute, Department EMD, INSERMU1016, Paris,
France and Medical Faculty, Paris University, Paris,
France, E-mail: phoweiss@gmail.com
Received: 09 Mar 2022
Accepted: 31 Mar 2022
Published: 06 Apr 2022
J Short Name: ACMCR
Copyright:
©2022 Pamela Houeiss. This is an open access article
distributed under the terms of the Creative Commons
Attribution License, which permits unrestricted use, dis-
tribution, and build upon your work non-commercially.
Citation:
Pamela Houeiss, Prevalence and Determinants of Dis-
tress Among Residents During COVID Crisis. Ann Clin
Med Case Rep. 2022; V8(17): 1-15
http://www.acmcasereport.com/ 1
1. Abstarct
1.1. Background and Objectives
Residents are predisposed to develop distress, burnout, and de-
pression. With COVID-19, new stressful working conditions were
imposed. This study aims to assess the impact of COVID-19 on
residents’ wellbeing in France.
1.2. Methods
Residents completed an online survey assessing the sociodemo-
graphic characteristics, the workload, the work environment, the
burden, and the psychological impact of the pandemic. Wellbe-
ing, burnout, and depression were assessed using respectively the
Residents and fellows’ wellbeing index (RSWBI), the abbreviated
Maslach Burnout Inventory (aMBI) and the PHQ-9 questionnaire.
Analysis was done on SPSS 25. Variables were significantly
associated with the outcomes if p value ≤ 0.05.
1.3. Results
Thirty-four residents completed the survey. Their mean age was
28.4 years. Out of the respondents, 20.6% were at high risk for
distress, 56% were at moderate to severe risk for burnout and
27% had moderate to severe depressive symptoms. Being single
and work overload increased the risk of distress and burnout. Al-
though, COVID-19 did not affect the prevalence of distress and
burnout, it increased the intensity of the stress. Residents were
concerned about the repercussions that the pandemic might have
on their training and on their future. Higher wellbeing index was
significantly associated with poorer quality of life (p=0.001), high-
er regrets (p=0.004) and lower satisfaction (p=0.043) on the pro-
fessional level.
1.4. Conclusion
COVID-19 had an indirect impact on residents ’wellbeing. The
interruption of courses, the compromised training and the social
isolation contributed to residents’ burnout and distress. The reme-
dy would be to create a wellness program that promotes self-care
and resilience.
2. Introduction
Physician wellness is a topic of much concern. It is emerging as an
important indicator of the quality of medical programs [1]. Well-
ness as defined by EcKleberry-Hunt and colleagues is “a dynamic
and ongoing process involving self-awareness and health choices
resulting in a successful balanced lifestyle” [2]. Becoming a physi-
cian comes with sacrifices and challenges but it doesn’t mean that
one needs to suffer during the process. Despite rising the aware-
ness and recognizing the importance of physician wellness, the
prevalence of burn out, depression and suicidal ideation is higher
among resident physician than the general population3. In fact,
residents spend [3-7] years of their lives specializing in a medical
field of interest. They are exposed to stressful and traumatic situ-
ations that comes with limited control and high responsibilities.
They experience pain and death; they have long duty hours, and
they are preoccupied by their training and their future while facing
their personal insecurities. With these overwhelming stressors and
always feeling the need to compete and to be the best, maintain-
ing residents’ wellbeing and avoiding burn-out become hard and
challenging. The prevalence of burnout among residents in the US
varies between 27 and 75% depending on their specialty4. The
prevalence of burnout in the European countries is around 27.72%
(95% CI: 17.4–41.11)5. In the US, 28.8% of residents have de-
pressive symptoms6. In France, 10% of the residents have suicidal

Volume 8 Issue 17 -2022 Research Article
ideation. Furthermore, the incidence of suicides among residents
is 3 times higher than the general population with an incidence of
33 per 1000007. The harmful impact of distress is not limited to
residents. It may also affect patient care, and health care systems.
The effects include lower physician productivity, increased medi-
cal errors, longer recovery time, and lower patient satisfaction. As
if all these stressors were not enough, in 2020, Health care profes-
sionals (HCP) were facing a new challenge. SARS COV-2 virus
(COVID-19) spread, and the world was facing a global pandemic
with more than 4 million deaths. Residents were on the frontlines
providing care to infected patients. In the light of the uprising cri-
sis, they had to work overtime and stay away from their families.
Some were redeployed to other services, while others had their
courses cancelled. Studies showed that Covid-19 had an impact on
HCP burnout, but few studies checked the effect of the crisis on
residents’ wellbeing [8,9]. This survey focuses on the prevalence
of distress, burnout, and depression among residents in France
during the pandemic. It also investigates the impact of COVID-19
related factors on residents’mental health, and it assesses its reper-
cussion on residents’personal, social and professional lives. These
data will allow the conception of new strategies in the residency
programs to promote wellness and prevent burnout.
3. Materials and Methods
3.1. Study Design
A cross sectional study was conducted among residents in hospi-
tals in France between May and September 2021.An online survey
designed in google forms was diffused via email, WhatsApp, and
social media to reach as many residents as possible. An abstract
on the study and its purpose were provided on the first page of
the survey. Residents who filled the questionnaire were assumed
to have given their consent to take part in this study. Data was
collected anonymously without any potential identifier to protect
confidentiality.
3.2. Study Population
Residents were defined as those who are doing a specialty after
graduating from medical school. The inclusion criteria were a resi-
dent working in a hospital in France during the past year and will-
ing to participate in this study. Any participant who did not fulfill
the latter criteria was excluded.
3.3. Study Instruments
An online survey addressed to residents was developed using
previously validated instruments. The self-administered question-
naire covered four areas: the socio-demographic characteristics,
the work conditions, the impact of COVID-19 and the residents’
mental health.
3.4. Primary Outcome
The prevalence of distress, burnout and depression among resi-
dents were calculated based the Resident/Fellow Well-Being Index
(RSWBI), the abbreviated Maslach Burnout Inventory (aMBI) and
the Patient Health Questionnaire (PHQ-9) respectively. A- Wellbe-
ing: The survey utilized the RSWBI, a Mayo clinic validated 7 yes/
no questions tool to assess residents’ wellbeing [10]. The scores
range from 0 to 7. Based on a national survey, the mean score is
2.53 and the median is 2. Residents with a score of 5 or more are in
distress and are at higher risk for depression, burnout, and suicide.
B- Burnout: Burnout was assessed with the use of the modified a
MBI [11,12]. It uses a three‐item screening questions for each of
the three dimensions: emotional exhaustion (EE), depersonaliza-
tion (DP), and personal achievement (PA). Each question uses a 7
item Likert scale, and scores go from 0 (never) to 6 (always). Each
component of burnout scores from 0 to 18. A score above 9 on
EE or DP means that residents have moderate to severe emotional
exhaustion and depersonalization. Whereas if they score 0-9 on
PA, they have a low sense of personal achievement. Residents are
considered to have burnout when they have one abnormal score
in these subscales. C- Depression: The severity of depression was
assessed using the validated PHQ-913. The score can go from 0 to
27 with each item being attributed a number from 0 to 3 depending
on the frequency of occurrence of the described symptom. A cutoff
of ≥5 identify the presence of any depression related symptom and
a cut-off of ≥10 identify a moderate to severe depression.
3.5. Secondary Outcome
The association between the study variables and wellbeing, burn-
out and depression scores were tested to identify possible risk
factors. The repercussion of the residents’ wellness status on the
different aspects in life were assessed.
A- Sociodemographic characteristics: data on the age, the gender,
the nationality, the household status, and the marital status were
collected. B- Workload: Residents were asked about their weekly
schedule and about having extracurricular activities. Sleep depri-
vation was defined as residents sleeping less than 7 hours per day.
The Workload score was based on working hours (overtime, work-
ing more than 60 hours/week, duty hours/ week), on work inten-
sity score, on sleeping hours and on the interactions with patients.
One point was attributed to each item except for the work intensity
score in which 1 point was attributed for the values [6-7], and 2
points were attributed to the values [8] and above. C- Work en-
vironment: To assess the work environment, 5-point Likert scale
questions on teamwork, level of communication and the amount
of contribution to decision making were used. Also, mistreatment
was assessed by reporting the frequency of exposure to any type
of discrimination during this year of residency. Residents were
classified by the maximum reported frequency of any of the mis-
treatment exposure into no exposure, exposure a few times/year
and exposure few times/ month14. The validated mayo clinic lead-
ership behavior score was also used. Each item in this score has a
5 point-Likert scale to assess the behavior of the residents’ super-

visors during their rotations15. The score ranges from 0 to 32 with
the highest score indicating better leadership skills. D- Working
conditions during COVID-19: To assess the residents’ experience
with COVID-19, questions on their exposure to sick patients, on
their fear and readiness to face this pandemic, on the availabil-
ity of protective equipment and on the support provided by the
hospital were asked. Also, the repercussion of COVID-19 on the
residents’ training, courses, financial status, health, and social life
was evaluated. E- Stressors and coping strategies: Residents were
requested to grade from 0 to 100, the stress level before and during
COVID-19. Multiple choice questions on the factors contributing
to their mental stress and on their coping behaviors were asked.
F- Repercussion on residents’ lives: Residents were asked if they
had any suicidal ideas in the past year16. They were also asked
simple yes/no questions to check if they abused alcohol, tobacco,
drugs, or medications during the past year. The validated one-item
7point Likert type scale was used to assess the residents’quality of
life (QoL-1) [17]. The score ranges from 1 (low or negative) to 7
(high or positive). Residents with scores below 4 had a low quality
of life. Those with a score of 4 had an average QOL and those with
scores above 4 had a good quality of life. A 5-point Likert scale
was used to assess the level of satisfaction in their residency pro-
gram, in their carrier choice and in their work life balance. It went
from very unsatisfied to very satisfied. Residents were allowed to
express freely any other opinion related to their wellbeing.
3.6. Statistical Analysis
Data analysis was done using the Statistical Package for Social
Sciences (SPSS) version 25 (IBM, USA). Sociodemographic
characteristics of the study population were determined using de-
scriptive statistics. Results of descriptive statistics were reported
using mean ± standard deviation (SD) for the continuous variables
and frequency or percent for the categorical values. The endpoint
variables (wellbeing, burnout, and depression) were the dependent
variables. Each endpoint was computed into a continuous and a
categorical variable as described earlier. The association between
the dependent and the independent variables was evaluated us-
ing independent T test, one-way ANOVA or Pearson correlation
when the sample’s size allowed it and with the non- parametric
Kruskal Wallis, Mann Whitney U and spearman correlation tests
when N<30. The Khi square and the Fischer exact test were used
to assess the association between two categorical variables. A sig-
nificant p value was set at 0.05. At first, the prevalence of distress,
burnout, and depression among participants was assessed. The
mean and median of RSWBI were compared to the values from
the general population using respectively the one sample T test and
the one sample Wilcoxon signed rank test. The baseline character-
istics and the working conditions of residents and their association
with the endpoints were checked. I only show the results using
continuous dependent variables. In the second part, a univariate
analysis studies the COVID related working conditions and their
association with wellbeing, burnout, depression and stress differ-
ence. The third analysis focused on the stressors and coping tech-
nique adopted by the participants during the pandemic. The last
one showed the repercussion of the three endpoints on the quality
of life, on the presence of suicidal ideation, on the development of
abusive behavior and on the level of satisfaction among residents.
A multivariate analysis was planned but was not feasible due to the
low number of participants.
4. Results
4.1. Baseline Characteristics and General Working Conditions
Despite reaching out to many hospitals, only 34 residents complet-
ed the survey. The response rate couldn’t be estimated since we
don’t know the exact number of residents that got the link of the
questionnaire. Most respondents were females and were originally
from France. Their mean age was 28.4 years. Of the respondents,
59% were in a relationship, 61.8% were sharing their apartments
with a family member, a partner, or a roommate and 14.7% had
kids (Table1). Participants were mainly working in hospitals lo-
cated in Paris and its suburbs with only 15.1% working in Lyon
or Bordeaux (supp Figure 1). The majority were in post-gradu-
ate year 3 (84.8%) (supp Figure 2). 69.7% were specializing in
non-surgical specialties (supp Figure 3). In their last rotation, resi-
dents were equally assigned to a surgical or a medical service with-
in which 65% admitted critical patients. On average, they were
taking care of 28 patients/week. Around 38% of residents claimed
to have a limited interaction with their patients. Among the partici-
pants, 44% were working more than 60 hours per week, 50% were
sleeping less than 7 hours/ day, 70% had to take courses and 35%
had to participate in lab research in addition to their usual tasks.
When asked about the frequency of working overtime, almost 41%
of residents answered frequently or every day. When asked about
work intensity on a scale from 0 to 10, 41% attributed a score of 8
or more (supp Figure 5). When it comes to the work environment
80% of the residents reported having a good dynamic within the
team and 70% reported a possibility to assist in decision making
(supp Figure 6). 30% were subject to discriminations based on gen-
der, on race, on pregnancy status and/or on origin. The nature of
the abuse was either verbal (60%) and/or emotional (40%) and/or
sexual (30%) (Table1). The residents were also asked to assess the
leadership skills of their supervisor. Around 50% agreed that their
supervisor held career development conversations with them, rec-
ognized them for a job well done and took the time to inform them
about the changes occurring in the division. Around 65% agreed
that their supervisor encouraged them to do their job and gain
experience and provide them with helpful feedback. 82% agreed
that the supervisor respected them and treated them with dignity
(Supp Figure 7). Prevalence of distress, burnout, and depression
during COVID-19 crisis. The average wellness index score in all
participants was 3 (SD=1.7) with 20.6% being at greater risk to
have a distress related personal or professional consequence. The

median of RSWBI during COVID- 19 was significantly higher
than the norm (Median: 3 v/s 2, p=0.003) (supp Figure 10). Using
the aMBI score (supp Figure 11-12) to assess the risk of burnout,
35.3% of residents were having a moderate to severe emotional
exhaustion, 29.4% had low sense of personal accomplishment and
11.8% had moderate to severe depersonalization (Figure 1B). In
total, 56% of residents were at risk for burnout. The higher risk
of burnout correlated best with EE (r=0.841, p<0.001) followed
by DP (r=0.739, p<0.001) and PA (r-0.56, p=0.001). The risk of
depression among residents was evaluated with the PHQ9 score.
70% of participant had depressive symptoms with 6% having se-
vere symptoms and requiring further assessment (Fig 1C). Of the
85% who had an issue with at least one item in the PHQ9, 62%
acknowledge a repercussion on their tasks at work and at home
and on their social life (supp Figure 8). Wellbeing index correlat-
ed significantly with PHQ9 score (r=0.62, p<0.001) and burnout
(r=0.546, p=0.001). Figure 1A shows the distribution of the an-
swers for each measured item in the wellbeing index. COVID in-
dependent factors affecting residents’ wellbeing Age, gender, and
nationality had no significant effect on wellbeing. Being in a re-
lationship rather than single decreased the risk of distress (OR=
[0.007-0.681]), burnout, and depression with p <0.05). Having a
partner was associated with higher sense of personal accomplish-
ment as compared to not having one (mean PA score=12.9 v/s 9.9,
p=0.02). Similar results were observed when comparing residents’
living arrangement; those who lived with their family or their part-
ner or a roommate had a lower risk of being in distress, they were
less emotionally exhausted and depersonalized, and they had high-
er sense of accomplishment thus lower risk of burnout and depres-
sion (p<0.05). Having kids tends to increase the sense of accom-
plishment (mean PA score: 14.4 v/s 11.2, p=0.08) and to protect
the residents from depersonalization and burnout (mean DP score:
2.4 v/s 4.1 p=0.36 and mean aMBI=13.8 v/s 19.5 p=0.17). The
level of training and the specialty were not significantly associated
with increased distress, despite data showing that surgery residents
and newly comers are more predisposed to experience burnout.
Rotating in surgical services increased the risk of burnout (p=0.03)
with 2 times higher risk of depersonalization (p=0.03). The de-
terminants of the work environment did not show any correlation
to the residents’ wellbeing. However, the composite variable of
the workload showed that the higher the workload, the higher is
the risk of distress (r=0.44, p=0.009) and emotional exhaustion
(r=0.37, p=0.03). These results are shown in Table1.
Table1: Baseline Characteristics of the resident physicians and their association with RSWBI, aBMI (EE, DP, PA) and PHQ9
All
participants
%(N) or
mean(SD)
Residents
with
Wellness
score>=5 %
(N)
Average
wellness index
Mean(SD)/R
EE
Mean(SD)/R
DP
Mean(SD)/R
PA
Mean(SD)/R
aBMI
Mean(SD)/R
PHQ9 score
Mean(SD)/R
Total N=34 N=7 3(1.7) 8.5(4.3) 3.8(3.6) 11.7(3.8) 18.6(8.5) 6.9(4.5)
Age
Mean(SD) 28.4(2.9) 28.3(3.2) r=0.01 r=0.21 r=0.07 r=0.11 r=0.09 r=0.27
Gender
Men 29.4(10) 42.9(3) 2.9(1.8) 8.5(3.8) 5.5(4.2) 12.4(3.9) 19.6(7.2) 6.7(4.2)
Woman 70.6(24) 57.1(4) 3.1(1.7) 8.5(4.6) 3.1(3.2) 11.4(3.8) 18.2(9.1) 6.9(4.6)
Nationality
French 67.6(23) 71.4(5) 2.9(1.8) 8(4.3) 3.9(3.7) 12(3.5) 17.9(8.6) 6.5(4.3)
Other 32.4(11) 28.6(2) 3.2(1.5) 9.6(4.3) 3.6(3.7) 11(4.5) 20.3(8.2) 7.5(4.9)
Marital Status
Single 41.2 (14) 85.7(6)* 3.8(1.7)* 9.8(4.1) 4.4(4.2) 9.9(3.9)* 22.3(8.1)* 8.7(4.5)*
Married/Couple 58.8(20) 14.3(1) 2.4(1.5) 7.6(4.3) 3.3(3.2) 12.9(3.3) 16.1(7.9) 5.5(4.1)
Kids
Yes 14.7(5) 14.3(1) 3.2(1.9) 7.8(4.6) 2.4(2.5) 14.4(4.8) 13.8(6.7) 7.8(5.9)
No 85.3(29) 85.7(6) 3(1.7) 8.6(4.3) 4.1(3.8) 11.2(3.5) 19.5(8.5) 6.7(4.3)
Living arrangement
Alone 38.2(13) 71.4(5) 3.8(1.7)* 10.7(3.9)* 5.6(4.4)* 9.3(3.2)** 25(6.4)** 8.7(4.8)
With partner/family/
roommate
61.8(21) 28.6(2) 2.5(1.6) 7.2(4.1) 2.7(2.6) 13.1(3.5) 14.7(7.1) 5.7(3.9)
Level of training (N=33)
<= 2 years 15.2(5) 42.9(3) 4.2(2.6) 10.6(4.8) 5.2(5.2) 10.8(4.8) 23(11.3) 9.6(5.2)
>2 years 84.8(28) 57.1(4) 2.8(1.5) 8.4(4) 3.7(3.4) 11.6(3.6) 18.5(7.4) 6.5(4.2)
Specialty (N=33)
Medical 69.7(23) 66.7(4) 2.8(1.6) 8.1(4) 3.3(3.2) 12.6(3.7) 16.9(8.3) 6.4(4.1)
Surgical 30.3(10) 33.3(2) 3.2(2) 9.5(5.2) 4.7(4.7) 10.2(3.3) 22(8.3) 7.5(5.3)
Current rotation (N=32)
Medical 53.1(17) 57.1(4) 3.1(1.6) 7.9(4.2) 2.5(3.3)* 12.9(4) 15.5(7.9)* 6.3(4.4)
Surgical 46.9(15) 42.9(3) 2.9(2) 9.2(4.8) 5.4(3.7) 10.6(3.3) 22(8.4) 8(4.5)
Composite
Workload scorea
(0-8) 3.7(2) 5.4(2.1)** R=0.44** R=0.37* R=0.13 R=0.11 R=0.13 R=0.17

Work environment
Team dynamics index
(0-12)b 9.6(1.7) 9.4(1.9) R=-0.08 R=-0.28 R=-0.14 R=0.22 R=-0.31 R=-0.25
Leadership index (0-32) 18.7(5.4) 17.4(8.4) R=-0.11 R=-0.183 R=-0.21 R=0.09 R=-0.22 R=-0.03
Discrimination
No 70.6(24) 71.4(5) 3(1.5) 8.3(3.9) 3.5(3.5) 11.9(3.8) 17.9(8.1) 6.7(4.1)
Few times/year 26.5(9) 28.6(2) 3(2.4) 9.4(5.4) 4.7(4.3) 11.9(3.5) 20.2(10.3) 7.1(5.8)
Few times/month 2.9(1) 0(0) 3(0) 5(0) 3(0) 5(0) 21(0) 8(0)
a
workload score is the sum of sleeping hours, working hours, duty hours, work intensity, working overtime and interaction.
b
Team dynamics index is the sum of the 3 variables: communication and coordination, decision making and getting along with the team. *if 0.001 <p
value< 0.05, ** if p value<=0.001
Figure 1: Classification of residents by place of residence
Figure 2: Classification of respondents by residency year
Figure 3: Classification of respondents by their specialty

Figure 4: classification of residents by nationality
Figure 5: Workload among residents
Figure 6: Team dynamics during residents’ last rotation

Figure 7: Residents’ responses to leadership items
Figure 8: Repercussion of depression on daily activity
Figure 9: Distribution of stressors by mental health status
Figure 10: Compromised elements in training during COVID-19

Figure 11: Differences in the medians before and during COVID using the One sample Wilcoxon signed rank test
Figure 12: Residents’ responses to aMB per item
Figure 1: Prevalence of distress, burnout, and depression during COVID_19. A-Wellbeing index responses to each item by resident physicians during
the COVID-19 pandemic. B- Severity of the symptoms of the 3 dimensions in the abbreviated MBI. C- Depressive symptoms classification as per the
PHQ9 questionnaire. (EE= emotional exhaustion, DP= depersonalization, PA= personal achievement, MBI=Maslach Burnout inventory).

5. COVID Direct Effect on Residents
Among participants, 88.2% took care of COVID-19 patients main-
ly inpatients on regular floors and in the ICU, for an average period
of 6 months. 43.3% were involved in treating these patients during
the 3 waves. 73.3% worked with infected patients during the third
wave. They were seeing on average 6 patients/day. Table 2 de-
scribes in detail the personal, emotional, and professional situation
of residents during COVID-19. These COVID related variables
had no significant effect on residents’ wellbeing, burnout, or de-
pression (supp Figure 15). However, the RSWBI was the high-
est in those who did not manage COVID patients and those who
treated COVID positive patients for at least 2 waves including the
third wave. The lowest score was seen in those who only worked
during the last wave (Figure 3A). Reversed variations were seen
with burnout (Figure 3B). During the crisis, residents were more
stressed. (r=0.43 p<0.001). The mean stress intensity increased
from 52.2(SD=23.9) before COVID-19 to 70.7 (SD=22.1) during
COVID-19 (Figure 2A). The fear from acquiring the disease and
the change in workload were significantly associated with the in-
crease in stress (Mean increase (fear/no fear) 27.3 v/s 5.3 p=0.029
and Median 15 v/s 5 p=0.037) (Figure 2B-C). In residents’ opin-
ion, the most important stressors during the past year were taking
care of patients (23.5%) and planning the future (23.5%). Only
14.7% chose COVID-19 as a major source of stress (Figure 4A). It
was a common stressor among residents at risk for burnout, where-
as the other two stressors were common among residents at risk for
depression or distress (supp Figure 9). Most residents (76.9%) felt
that their education and training were compromised by the crisis in
many aspects (Table 2). Explicitly, residents were concerned about
missing training, losing educational opportunities, and lacking
professional development which might affect their future. Some
were also frustrated about not having the time to grief (supp Figure
10). Talking to family and colleagues was the most common strat-
egy adapted by residents to deal with the stressors (Figure 4B).
Figure 13: Summary of aMBI answers
Figure 14: Wellbeing, burnout, and depression scores variations with the COVID related Factors

Figure 15: Quality of life and satisfaction
Figure 2: COVID-19 effect on stress intensity. A-Intensity of stress increases during COVID-19. B- The increase in workload due to COVID-19
increases the stress intensity. C- The fear from acquiring COVID-19 increases the stress intensity.
Figure 3: Changes in Wellbeing and burnout status with the exposure to COVID positive patients. Graphs showing the variation of the wellbeing index
(A) and of the Burnout index (B) with the amount of exposure to COVID positive patients (Number of waves) and the freshness of the exposure (ex-
posure to third wave). Results are presented by the mean RSWBI or the mean aBMI for each category.
Figure 4: Stressors and coping mechanisms during COVID-19. A-Repartition of stressors among the residents during COVID-19. B- coping mecha-
nisms responses by residents during COVID-19.

Table 2: Residents’ working conditions during COVID-19
ALL PARTICIPANTS %(N)
TREATING COVID PATIENTS (N=34)
YES 88.2(30)
NO 11.8(4)
IF YES
WAVES (N=30)
FIRST 73.3(22)
SECOND 73.3(22)
THIRD 73.3(22)
LAST WAVE (N=30)
YES 73.3(22)
NO 26.7(8)
DURATION IN MONTHS MEAN (SD) N=19 5.9(4.7)
UNITS (N=29)
OUTPATIENT 17.2(5)
EMERGENCY DEPARTMENT 24.1(7)
OR 6.9(2)
INPATIENTS FLOOR 55.2(16)
INTENSIVE CARE 41.4(12)
LABORATORY 3.4(1)
NUMBER OF PATIENTS/DAY MEAN (SD) N=19 5.7(4.5)
All participants
LOSS OF A FAMILY MEMBER(N=34)
YES 20.6(7)
NO 79.4(27)
AWAY FROM FAMILY(N=34)
YES 73.5(25)
NO 26.5(9)
CAUGHT COVID(N=34)
YES 17.6(6)
NO 82.4(28)
READINESS TO FACE THE CRISIS MEAN (SD) N=32 5(2.8)
FEAR OF HAVING COVID (N=34)
YES 50(17)
NO 50(17)
PROTECTIVE EQUIPMENT (N=34)
YES 82.428)
NO 17.6(6)
SUPPORT IN THE HOSPITAL(N=34)
YES 79.4(27)
NO 20.6(7)
CHANGES IN PROFESSIONAL ACTIVITY (N=34)
YES 85.3(29)
NO 14.7(5)
COMPROMISED EDUCATION (N=26)
YES 76.9(20)
NO 23.1(6)
DEPLOYMENT(N=34)
YES 67.6(23)
NO 32.4(11)
CHANGE IN WORKLOAD(N=34)
NO 20.6(7)
INCREASED 58.8(20)
DECREASED 20.6(7)
CHANGE IN FINANCIAL SITUATION (N=34)
YES 14.7(5)
NO 85.3(29)
5.1. The Repercussion of Residents’ Wellness During COVID
Crisis on Their Lives.
Being in distress can affect many dimensions in life. On a psycho-
logical level, 8.8% of respondents had suicidal ideation at least
once during the last year. 29.4% of residents managed their dis-
tress by the substance abuse mainly alcohol and smoking (supp
Figure 16). These psychological disorders were not significantly
associated with neither the RSWBI, nor the aMBI, nor the PHQ9
score (data not shown). On a personal level, 41.2% of the resi-
dents described their quality of life by being good, whereas 32.4%
saw that their life was somewhat distressing (supp Figure 15A).
The quality-of-life scale was inversely correlated to the wellbeing
index (r=-0.53, p=0.001) (Figure 5B). Any worsening emotional
exhaustion, any increase in the risk of burnout and any increase

in the risk of depression were significantly correlated to a poor-
er QOL (r (EE)=-0.41, p=0.02, r(aMBI)=-0.41, p=0.02, r(PHQ9)
=-0.65, p<0.001). On a professional level, almost half of the par-
ticipants regret at least sometimes their choice to pursue a degree
in medicine (supp Figure 15B). Residents with regret have a high-
er aMBI index (r=0.49, p=0.004) and a higher level of emotion-
al exhaustion (r=0.55, p=0.001) (Fig 5D). On another level, all
residents were not satisfied with their residency program, 17.7%
were disappointed with their training and 20.6% were undecided
(supp Figure 15D). The level of satisfaction of the residency pro-
gram is significantly associated with the wellbeing index (r=- 0.49,
p=0.003), with the risk of burnout (r=-0.52, p=0.002) mainly with
EE (r=-0.48, p=0.004) and PA (r=0.45, p=0.008) and with the risk
of depression (r=-0.55, p=0.001) (Figure 5C). On a social level,
almost half the residents (41.2%) acknowledge that they couldn’t
maintain a work-life balance during the last year in training (supp
Figure 15C). The lack of work life balance is significantly asso-
ciated with a high RSWBI (r=-0.47, p=0.005), a high aMBI (r=-
0.48, p=0.004), a high PHQ9 (r=-0.62, p<0.001), a high EE score
(r=- 0.37, p=0.032) and a Low PA score (r=0.42, p=0.013) (Figure
5E).
Figure 16: Substance abuse among residents
Figure 5: Repercussion of residents’ wellness status on mental health, quality of life and satisfaction. AVariations of indexes in the presence of suicidal
ideation. B- Quality of life inversely correlates with wellbeing, depression, and burnout (1 to 6 with 6 being perfect). C- Residents are satisfied with
their residency program with a lower risk of distress, depression, and burnout. D- Residents shows more regrets with their choice when they are at risk
of burnout. E- The better the work life balance, the lower the risk of depression, burnout, and distress. *if 0.001 <p value< 0.05, ** if p value<=0.001
6. Discussion
This survey of 34 residents revealed that during COVID-19, the
respondents are at a higher risk of distress regardless of the expo-
sure to COVID positive patients. The workload and the family sta-
tus affected the residents’ wellbeing. From the COVID-19 related
factors, none was significantly associated to the wellbeing, burn-
out, and depression scores. However, fear from getting the dis-
ease and the increased workload were associated with an increased
stress. During the crisis, residents were mainly concerned about
the interruption of the educational activities and the repercussion
of the whole situation on their future career. The distress put them
at risk for substance abuse, it compromised their quality of life
and the level of satisfaction of the work-life balance. Impact of
COVID on the prevalence of Wellbeing, Burnout, and depression.
During the crisis, residents scored higher on the wellbeing index.
It is difficult to compare the values observed in this study to the
ones from other studies due to the heterogeneity of the used index-
es. However, similar mean RSWBI values and higher at-risk per-
centages were observed in a study conducted during COVID-19
among US residents when using the same index (mean=2.84+-
2.04, at-risk=24%)18. The report of 2020-2021 from Mayo clinic
showed that out of the 9,164 assessed residents and fellows from
the world, 16.4% were at high risk for distress. The differences
in at risk percentages can be explained by the regional variation

of medical programs and COVID-19 burden. Burnout is one of
the dimensions in wellbeing; it correlates with wellbeing without
being similar. Despite the previous study showing increased res-
idents’ burnout during the pandemic19, the prevalence of burn-
out in this study was unchanged. The calculated frequency is in
the range of values obtained from other studies before and during
COVID-193, 19, 20. Nevertheless, COVID-19 did influence the
burnout dimensions. During the pandemic, residents mostly expe-
rienced high emotional exhaustion. This was not the case before
COVID-19. Results from the national Bourbon study showed that
junior residents report high prevalence of depersonalization (30-
38%) and of low personal accomplishment (29-42%) and lower
prevalence of emotional exhaustion (12-29%)21. This is consis-
tent with a study on medical and surgical residents showing that
50% have severe loss of empathy22. During COVID-19, residents
worked under pressure which might explain the high emotional
exhaustion. However, working during this crisis could have been
rewarding. Actively helping patients to recover and to rejoin their
family could have increased the sense of accomplishment. Well-
being also correlates with depression. In this study, physicians in
training were at a higher risk for depression. Before the pandemic,
a systematic review showed that the prevalence of moderate to se-
vere depressive symptoms was 20.9%6. This prevalence increased
to 27% during COVID-19. Residents were in a situation where
they must face death and fear on daily basis while being isolated
from their support system. During COVID-19, HCP in India in-
cluding residents were having similar issues23.
6.1. Risk Factors for Distress, Burnout, and Depression
During a pandemic, Health care workers are prone to develop dis-
tress reactions, psychiatric disorders and health risk behaviors as
opposed to becoming resilient [24]. This is secondary to the pre-
event, the event, and the post-event risk factors. In this study, when
looking into the pre-event risk factors, it was shown that residents
rotating in surgery are at higher risk for burnout manifesting as
depersonalization. Work overload exposed residents to emotional
exhaustion leading to distress. Additionally, work environment
was not always optimal, many residents were not having their su-
pervisor’s guidance and encouragement to ease their stress and to
improve their skills. On a different level, having family support
and not living alone protected the residents by increasing the sense
of accomplishment and limiting depersonalization, and therefore
burnout. The current literature showed that besides autonomy and
competence building, strong social support is associated with resi-
dents’ wellbeing [3]. These observations are concordant to the re-
sults from studies on the risk factors of burnout among residents
[3,25]. In a disaster, the duration and the severity of exposure can
affect the psychological outcome26. During the crisis, COVID-19
was not the most important contributor to distress and burnout.
Although a study done on residents showed that the greater expo-
sure to patients with COVID-19 and the access to adequate protec-
tive equipment predict burnout [19], none of these factors correlat-
ed with wellbeing and burnout in this study. It is possible that the
limited number of participants, the difference in the exposure’s
severity per specialty [27] and the different timing in exposure di-
luted the impact of COVID-19 on residents ‘wellbeing. When
classifying Wellbeing and burnout indexes by the number of waves
and by being actively involved in treating patients during the last
wave, a discordance was seen between the groups. Residents who
didn’t treat COVID-19 patients or those who treated patients
during the 3 waves had a low burnout index compared to those
who worked with COVID-19 patients for the first time during the
last wave. On the other hand, these observations were reversed
when checking the distress levels. Burnout and wellbeing vari-
ables correlate, but they are not equivalent. By treating patients
during 3 waves, residents were more autonomous and more confi-
dent when handling these patients. Additionally, the advances in
the understanding of the disease, the development of the vaccines
for prevention and the decline in the incidence of severe cases al-
leviated the disease’s burden. Being actively engaged during the
crisis induced a sense of fulfillment. Nevertheless, this doesn’t
mean that residents were not suffering. Someone said: “in a disas-
ter, the size of psychological footprint greatly exceeds the size of
the medical footprint”28. Those who worked this long with
COVID-19 patients did not have the time to grief, to reflect, to
process and to rebuild. On the other hand, residents who never
worked with COVID-19 patients were not at risk for burnout, but
they did suffer from the course’s cancellation and from the social
isolation. Also, they didn’t take part in fighting the pandemic and
they didn’t experience the fulfillment from saving lives. These ob-
servations were also found by Dimitriu et al; residents who were
involved in treating COVID-19 patients had less burnout than
those who were not [29]. During COVID-19, the intensity of stress
increased, and it correlated with burnout and wellbeing. Residents
worried most about managing the patients. On one hand, they were
afraid from acquiring COVID-19 and on the other hand, they
worked in saturated services while lacking evidence on the man-
agement of COVID-19. Residents were also preoccupied by their
career. They felt that their education and their training were com-
promised and that this would affect their skills in the future. Stress-
ing over the disease per say came second. Residents expressed
their concerns about their readiness but also their safety and the
safety of their loved ones. Social support was compromised during
this crisis; the majority stayed away from their family. Sanghavi et
al showed that social isolation negatively impacted residents ’well-
being with a 50% of resident experiencing anxiety during the pan-
demic [25]. With COVID-19 came a high morbidity and mortality
rates. Residents had to deal with the death of their patients and the
death of their loved ones. Nevertheless, the high turnover didn’t
allow them to have a time to grief. Coping was mainly by social
relatedness and seeking support from a family member, from col-

leagues or an expert. Nevertheless, some residents preferred social
isolation and managed their stress by switching their attention to a
solitary activity. In few instances, residents handled their stress
through the unhealthy self-soothing behaviors like alcohol abuse.
Suffering in times of crisis had a negative downstream effect on
the quality of life and on the level of satisfaction. Residents regret-
ted enrolling in medicine, and they were not satisfied with their
work-life balance. This shows the burden that a resident physician
might carry and explains why many of them end up withdrawing
and changing their major. During the pandemic, problems arouse
on many levels leading to a disturbed mental and physical health
[20,30]. In France, programs have been implemented to address
residents’ wellness. Residents in need have access to professional
help and psychological support. However, they are still reluctant,
even ashamed when it comes to acknowledge being in distress.
The small number of respondents in this study could reflect the
lack of interest, the lack of knowledge or perhaps the lack of trust
in the system and in its capacity to evolve. The high levels of dis-
tress and burnout indicates that this approach is not optimized to
promote wellness during a pandemic. The wellness programs im-
plemented around the world during the crisis focused on HCP
safety, social connectedness, and psychological support [31-33].
This survey identified some of the challenges that should be ad-
dressed in the wellness program. Thus, the need to intervene by
focusing on three approaches: target residents’ concerns and neu-
tralize the stressors, implement strategies to face future crisis and
promote residents’ recovery during and post-crisis. Residents saw
COVID-19 as a threat to their safety but also to their training.
Working on reorganizing the services and on limiting the contact
with patients without compromising the care would help support
residents. Sustaining a minimum of didactic sessions would give
them a sense of normalcy and stability. The work overload with the
limited time and resources requires efficiency and communication
at work; organizing regular meetings for updates on patients’man-
agement could help resident to stay current but also confident
when treating their patients. To prioritize wellness is to promote
self-care and resilience. Recognizing the signs of distress and
seeking help should become a habit. To promote self-care, a first
step would be to create a wellness group in each hospital. This
group would organize support meetings and social gatherings
where resident can connect with their peers and express their con-
cerns freely. This group would also educate residents on burnout
symptoms and would monitor the level of psychological distress
by regular wellness assessment. When needed, they would recom-
mend seeking an expert opinion. The COVID-19 crisis highlighted
the importance of leadership and mentorship. A mentor would help
the mentee in reaching their goals. He can offer advice, share his
experience, and support the medical trainers. Hospitals should also
contribute to maintaining residents’ wellbeing by allocating re-
sources and taking measures that would protect the healthcare pro-
fessionals in the future. Asking for feedbacks from HCP might
help in creating a protocol for managing patients during pandem-
ics. The general surgery program in the University of British Co-
lumbia have created a similar program that minimizes the addi-
tional stress caused by COVID-19, promotes the culture of well-
ness, and encourage resilience [34]. Despite not having numbers to
support the efficiency of these interventions, this program helped
surgical residents in gaining insights to their moral purpose and in
actively engaging to caring for the sick. In a study conducted in the
US, meal support, program mentorship, contact with leadership
and counseling services were considered very helpful. However,
these interventions didn’t improve the RSWBI scores and 34% of
the residents found them useless18. New studies should be con-
ducted to assess the best strategy in promoting wellbeing. There
are several limitations in this study. The small sample makes it
difficult to interpret the results. A selection bias might have been
introduced since the residents interested in this study might be
those who are having problems during their residency. Thus, the
association between COVID-19 and residents’ wellbeing might be
overestimated and is not generalizable. The survey included sub-
jective questions as well as questions requiring to remember events
which might lead to a recall bias. Also, questions on incidence of
COVID-19 related ICU admissions and mortality to assess the
workload at the time of answering the questionnaire were missing.
A causal relationship between risk factors, wellbeing, quality of
life and satisfaction cannot be established since it is a cross sec-
tional study. Nevertheless, this survey should be seen as a pilot
study showing that residents ’wellbeing is a serious problem that
needs to be addressed properly. Selection bias.
7. Conclusion
Even before the pandemic, residents faced distress, burnout, and
depression. COVID-19 did not influence the prevalence of distress
or burnout among residents, but it has increased the depressive
symptoms and the intensity of stress. Residents were deprived
from the family support and from the ability to acquire skills in
their field. The consequences were a decrease in the quality of life,
a regret of choosing medicine and a dissatisfaction of the work-
life balance. During these difficult times, the best way to support
residents and prevent psychological, social, and personal reper-
cussions is to create a wellness program that promote residents’
wellbeing.
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